Data profiling report

Dataset statistics

Number of variables	12
Number of observations	348
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	32.8 KiB
Average record size in memory	96.4 B

Variable types

Categorical	2
Numeric	10

Alerts

`year` has constant value "2016"	Constant
`temp_2` is highly correlated with `month` and 6 other fields	High correlation
`temp_1` is highly correlated with `month` and 6 other fields	High correlation
`average` is highly correlated with `month` and 7 other fields	High correlation
`actual` is highly correlated with `month` and 7 other fields	High correlation
`forecast_noaa` is highly correlated with `month` and 7 other fields	High correlation
`forecast_acc` is highly correlated with `month` and 7 other fields	High correlation
`forecast_under` is highly correlated with `month` and 7 other fields	High correlation
`friend` is highly correlated with `month` and 5 other fields	High correlation
`week` is highly correlated with `year`	High correlation
`year` is highly correlated with `week`	High correlation
`month` is highly correlated with `temp_2` and 7 other fields	High correlation
`day` is uniformly distributed	Uniform
`week` is uniformly distributed	Uniform

Reproduction

Analysis started	2022-09-27 15:32:36.421122
Analysis finished	2022-09-27 15:32:58.236564
Duration	21.82 seconds
Software version	pandas-profiling v3.3.0
Download configuration	config.json

year
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	2.8 KiB

2016	348

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	1392
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2016
2nd row	2016
3rd row	2016
4th row	2016
5th row	2016

Common Values

Value	Count	Frequency (%)
2016	348	100.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
2016	348	100.0%

Most occurring characters

Value	Count	Frequency (%)
2	348	25.0%
0	348	25.0%
1	348	25.0%
6	348	25.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1392	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	348	25.0%
0	348	25.0%
1	348	25.0%
6	348	25.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1392	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	348	25.0%
0	348	25.0%
1	348	25.0%
6	348	25.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1392	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	348	25.0%
0	348	25.0%
1	348	25.0%
6	348	25.0%

month
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	12
Distinct (%)	3.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.477011494

Minimum	1
Maximum	12
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.8 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	3
median	6
Q3	10
95-th percentile	12
Maximum	12
Range	11
Interquartile range (IQR)	7

Descriptive statistics

Standard deviation	3.498380066
Coefficient of variation (CV)	0.5401225657
Kurtosis	-1.236715006
Mean	6.477011494
Median Absolute Deviation (MAD)	3
Skewness	0.03675217283
Sum	2254
Variance	12.23866309
Monotonicity	Increasing

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
1	31	8.9%
3	31	8.9%
5	31	8.9%
7	31	8.9%
12	31	8.9%
4	30	8.6%
6	30	8.6%
10	30	8.6%
11	30	8.6%
9	28	8.0%
Other values (2)	45	12.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	31	8.9%
2	26	7.5%
3	31	8.9%
4	30	8.6%
5	31	8.9%
6	30	8.6%
7	31	8.9%
8	19	5.5%
9	28	8.0%
10	30	8.6%

Value	Count	Frequency (%)
12	31	8.9%
11	30	8.6%
10	30	8.6%
9	28	8.0%
8	19	5.5%
7	31	8.9%
6	30	8.6%
5	31	8.9%
4	30	8.6%
3	31	8.9%

day
Real number (ℝ_≥0)

UNIFORM

Distinct	31
Distinct (%)	8.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	15.51436782

Minimum	1
Maximum	31
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.8 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	8
median	15
Q3	23
95-th percentile	29
Maximum	31
Range	30
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	8.772981867
Coefficient of variation (CV)	0.5654746601
Kurtosis	-1.195389922
Mean	15.51436782
Median Absolute Deviation (MAD)	8
Skewness	0.04703994115
Sum	5399
Variance	76.96521084
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=31)

Value	Count	Frequency (%)
16	12	3.4%
9	12	3.4%
23	12	3.4%
15	12	3.4%
28	12	3.4%
12	12	3.4%
10	12	3.4%
11	12	3.4%
8	12	3.4%
7	12	3.4%
Other values (21)	228	65.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	11	3.2%
2	11	3.2%
3	12	3.4%
4	12	3.4%
5	12	3.4%
6	12	3.4%
7	12	3.4%
8	12	3.4%
9	12	3.4%
10	12	3.4%

Value	Count	Frequency (%)
31	6	1.7%
30	10	2.9%
29	10	2.9%
28	12	3.4%
27	11	3.2%
26	11	3.2%
25	11	3.2%
24	11	3.2%
23	12	3.4%
22	11	3.2%

week
Categorical

HIGH CORRELATION
UNIFORM

Distinct	7
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	2.8 KiB

Tues	52
Fri	50
Sat	50
Sun	49
Mon	49
Other values (2)	98

Length

Max length	5
Median length	3
Mean length	3.431034483
Min length	3

Characters and Unicode

Total characters	1194
Distinct characters	16
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Fri
2nd row	Sat
3rd row	Sun
4th row	Mon
5th row	Tues

Common Values

Value	Count	Frequency (%)
Tues	52	14.9%
Fri	50	14.4%
Sat	50	14.4%
Sun	49	14.1%
Mon	49	14.1%
Wed	49	14.1%
Thurs	49	14.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
tues	52	14.9%
fri	50	14.4%
sat	50	14.4%
sun	49	14.1%
mon	49	14.1%
wed	49	14.1%
thurs	49	14.1%

Most occurring characters

Value	Count	Frequency (%)
u	150	12.6%
T	101	8.5%
e	101	8.5%
s	101	8.5%
r	99	8.3%
S	99	8.3%
n	98	8.2%
F	50	4.2%
i	50	4.2%
a	50	4.2%
Other values (6)	295	24.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	846	70.9%
Uppercase Letter	348	29.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
u	150	17.7%
e	101	11.9%
s	101	11.9%
r	99	11.7%
n	98	11.6%
i	50	5.9%
a	50	5.9%
t	50	5.9%
o	49	5.8%
d	49	5.8%

Uppercase Letter

Value	Count	Frequency (%)
T	101	29.0%
S	99	28.4%
F	50	14.4%
M	49	14.1%
W	49	14.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1194	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
u	150	12.6%
T	101	8.5%
e	101	8.5%
s	101	8.5%
r	99	8.3%
S	99	8.3%
n	98	8.2%
F	50	4.2%
i	50	4.2%
a	50	4.2%
Other values (6)	295	24.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1194	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
u	150	12.6%
T	101	8.5%
e	101	8.5%
s	101	8.5%
r	99	8.3%
S	99	8.3%
n	98	8.2%
F	50	4.2%
i	50	4.2%
a	50	4.2%
Other values (6)	295	24.7%

temp_2
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	56
Distinct (%)	16.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	62.65229885

Minimum	35
Maximum	117
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.8 KiB

Quantile statistics

Minimum	35
5-th percentile	43.35
Q1	54
median	62.5
Q3	71
95-th percentile	81.65
Maximum	117
Range	82
Interquartile range (IQR)	17

Descriptive statistics

Standard deviation	12.16539811
Coefficient of variation (CV)	0.194173212
Kurtosis	0.3109757684
Mean	62.65229885
Median Absolute Deviation (MAD)	8.5
Skewness	0.2530289628
Sum	21803
Variance	147.9969111
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
60	16	4.6%
68	15	4.3%
57	14	4.0%
65	13	3.7%
71	12	3.4%
55	12	3.4%
67	11	3.2%
52	11	3.2%
64	11	3.2%
59	11	3.2%
Other values (46)	222	63.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
35	2	0.6%
36	1	0.3%
39	3	0.9%
40	5	1.4%
41	3	0.9%
42	3	0.9%
43	1	0.3%
44	5	1.4%
45	5	1.4%
46	4	1.1%

Value	Count	Frequency (%)
117	1	0.3%
92	1	0.3%
90	1	0.3%
89	1	0.3%
88	1	0.3%
87	2	0.6%
86	1	0.3%
85	4	1.1%
84	1	0.3%
83	2	0.6%

temp_1
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	56
Distinct (%)	16.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	62.70114943

Minimum	35
Maximum	117
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.8 KiB

Quantile statistics

Minimum	35
5-th percentile	43.35
Q1	54
median	62.5
Q3	71
95-th percentile	81.65
Maximum	117
Range	82
Interquartile range (IQR)	17

Descriptive statistics

Standard deviation	12.12054244
Coefficient of variation (CV)	0.1933065431
Kurtosis	0.3390438597
Mean	62.70114943
Median Absolute Deviation (MAD)	8.5
Skewness	0.2551268251
Sum	21820
Variance	146.9075491
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
57	16	4.6%
60	16	4.6%
68	15	4.3%
65	13	3.7%
71	12	3.4%
55	12	3.4%
67	11	3.2%
52	11	3.2%
64	11	3.2%
59	11	3.2%
Other values (46)	220	63.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
35	2	0.6%
36	1	0.3%
39	3	0.9%
40	5	1.4%
41	3	0.9%
42	3	0.9%
43	1	0.3%
44	4	1.1%
45	5	1.4%
46	4	1.1%

Value	Count	Frequency (%)
117	1	0.3%
92	1	0.3%
90	1	0.3%
89	1	0.3%
88	1	0.3%
87	2	0.6%
86	1	0.3%
85	4	1.1%
84	1	0.3%
83	2	0.6%

average
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	243
Distinct (%)	69.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	59.76063218

Minimum	45.1
Maximum	77.4
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.8 KiB

Quantile statistics

Minimum	45.1
5-th percentile	45.5
Q1	49.975
median	58.2
Q3	69.025
95-th percentile	77
Maximum	77.4
Range	32.3
Interquartile range (IQR)	19.05

Descriptive statistics

Standard deviation	10.52730643
Coefficient of variation (CV)	0.1761578826
Kurtosis	-1.315523428
Mean	59.76063218
Median Absolute Deviation (MAD)	9.25
Skewness	0.2320463885
Sum	20796.7
Variance	110.8241806
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
45.1	7	2.0%
77.3	7	2.0%
45.2	4	1.1%
45.3	4	1.1%
77.1	4	1.1%
48.4	3	0.9%
77.4	3	0.9%
77.2	3	0.9%
49.1	3	0.9%
76.9	3	0.9%
Other values (233)	307	88.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
45.1	7	2.0%
45.2	4	1.1%
45.3	4	1.1%
45.4	2	0.6%
45.5	2	0.6%
45.6	2	0.6%
45.7	2	0.6%
45.8	1	0.3%
45.9	2	0.6%
46	2	0.6%

Value	Count	Frequency (%)
77.4	3	0.9%
77.3	7	2.0%
77.2	3	0.9%
77.1	4	1.1%
77	2	0.6%
76.9	3	0.9%
76.8	2	0.6%
76.7	2	0.6%
76.6	2	0.6%
76.5	1	0.3%

actual
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	55
Distinct (%)	15.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	62.54310345

Minimum	35
Maximum	92
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.8 KiB

Quantile statistics

Minimum	35
5-th percentile	42.35
Q1	54
median	62.5
Q3	71
95-th percentile	81
Maximum	92
Range	57
Interquartile range (IQR)	17

Descriptive statistics

Standard deviation	11.79414614
Coefficient of variation (CV)	0.1885762856
Kurtosis	-0.5638304613
Mean	62.54310345
Median Absolute Deviation (MAD)	8.5
Skewness	0.02343610814
Sum	21765
Variance	139.1018831
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
57	16	4.6%
68	16	4.6%
60	16	4.6%
65	13	3.7%
71	12	3.4%
55	12	3.4%
67	11	3.2%
64	11	3.2%
59	11	3.2%
52	11	3.2%
Other values (45)	219	62.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
35	2	0.6%
36	1	0.3%
39	3	0.9%
40	6	1.7%
41	3	0.9%
42	3	0.9%
43	1	0.3%
44	4	1.1%
45	4	1.1%
46	4	1.1%

Value	Count	Frequency (%)
92	1	0.3%
90	1	0.3%
89	1	0.3%
88	1	0.3%
87	2	0.6%
86	1	0.3%
85	4	1.1%
84	1	0.3%
83	2	0.6%
82	3	0.9%

forecast_noaa
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	37
Distinct (%)	10.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	57.23850575

Minimum	41
Maximum	77
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.8 KiB

Quantile statistics

Minimum	41
5-th percentile	43
Q1	48
median	56
Q3	66
95-th percentile	75
Maximum	77
Range	36
Interquartile range (IQR)	18

Descriptive statistics

Standard deviation	10.60574637
Coefficient of variation (CV)	0.1852904129
Kurtosis	-1.235549844
Mean	57.23850575
Median Absolute Deviation (MAD)	9
Skewness	0.2506190341
Sum	19919
Variance	112.481856
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=37)

Value	Count	Frequency (%)
45	19	5.5%
44	16	4.6%
49	16	4.6%
48	15	4.3%
46	14	4.0%
47	14	4.0%
43	12	3.4%
62	12	3.4%
64	12	3.4%
66	11	3.2%
Other values (27)	207	59.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
41	5	1.4%
42	6	1.7%
43	12	3.4%
44	16	4.6%
45	19	5.5%
46	14	4.0%
47	14	4.0%
48	15	4.3%
49	16	4.6%
50	8	2.3%

Value	Count	Frequency (%)
77	4	1.1%
76	10	2.9%
75	8	2.3%
74	8	2.3%
73	8	2.3%
72	9	2.6%
71	8	2.3%
70	5	1.4%
69	5	1.4%
68	6	1.7%

forecast_acc
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	37
Distinct (%)	10.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	62.37356322

Minimum	46
Maximum	82
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.8 KiB

Quantile statistics

Minimum	46
5-th percentile	48
Q1	53
median	61
Q3	72
95-th percentile	79
Maximum	82
Range	36
Interquartile range (IQR)	19

Descriptive statistics

Standard deviation	10.54938117
Coefficient of variation (CV)	0.1691322514
Kurtosis	-1.30411627
Mean	62.37356322
Median Absolute Deviation (MAD)	9
Skewness	0.1973335282
Sum	21706
Variance	111.2894432
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=37)

Value	Count	Frequency (%)
51	18	5.2%
78	16	4.6%
50	15	4.3%
52	15	4.3%
49	13	3.7%
53	13	3.7%
56	13	3.7%
59	13	3.7%
48	12	3.4%
77	12	3.4%
Other values (27)	208	59.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
46	6	1.7%
47	7	2.0%
48	12	3.4%
49	13	3.7%
50	15	4.3%
51	18	5.2%
52	15	4.3%
53	13	3.7%
54	12	3.4%
55	6	1.7%

Value	Count	Frequency (%)
82	1	0.3%
81	6	1.7%
80	5	1.4%
79	9	2.6%
78	16	4.6%
77	12	3.4%
76	10	2.9%
75	8	2.3%
74	5	1.4%
73	10	2.9%

forecast_under
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	36
Distinct (%)	10.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	59.77298851

Minimum	44
Maximum	79
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.8 KiB

Quantile statistics

Minimum	44
5-th percentile	45.35
Q1	50
median	58
Q3	69
95-th percentile	77
Maximum	79
Range	35
Interquartile range (IQR)	19

Descriptive statistics

Standard deviation	10.70525553
Coefficient of variation (CV)	0.1790985493
Kurtosis	-1.261266441
Mean	59.77298851
Median Absolute Deviation (MAD)	9
Skewness	0.2534595539
Sum	20801
Variance	114.6024959
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=36)

Value	Count	Frequency (%)
49	24	6.9%
46	18	5.2%
55	17	4.9%
50	13	3.7%
48	12	3.4%
51	12	3.4%
65	12	3.4%
66	12	3.4%
77	12	3.4%
47	12	3.4%
Other values (26)	204	58.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
44	9	2.6%
45	9	2.6%
46	18	5.2%
47	12	3.4%
48	12	3.4%
49	24	6.9%
50	13	3.7%
51	12	3.4%
52	9	2.6%
53	9	2.6%

Value	Count	Frequency (%)
79	7	2.0%
78	9	2.6%
77	12	3.4%
76	8	2.3%
75	11	3.2%
74	5	1.4%
73	9	2.6%
72	5	1.4%
71	11	3.2%
70	7	2.0%

friend
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	66
Distinct (%)	19.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	60.03448276

Minimum	28
Maximum	95
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.8 KiB

Quantile statistics

Minimum	28
5-th percentile	35
Q1	47.75
median	60
Q3	71
95-th percentile	86.65
Maximum	95
Range	67
Interquartile range (IQR)	23.25

Descriptive statistics

Standard deviation	15.62617938
Coefficient of variation (CV)	0.2602867328
Kurtosis	-0.7053289416
Mean	60.03448276
Median Absolute Deviation (MAD)	11
Skewness	0.120703434
Sum	20892
Variance	244.1774819
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
56	14	4.0%
65	13	3.7%
70	12	3.4%
58	12	3.4%
61	12	3.4%
64	11	3.2%
62	11	3.2%
57	10	2.9%
54	10	2.9%
41	9	2.6%
Other values (56)	234	67.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
28	1	0.3%
29	2	0.6%
30	2	0.6%
31	1	0.3%
33	2	0.6%
34	5	1.4%
35	6	1.7%
36	3	0.9%
37	3	0.9%
38	7	2.0%

Value	Count	Frequency (%)
95	3	0.9%
94	1	0.3%
93	2	0.6%
91	1	0.3%
90	4	1.1%
89	2	0.6%
88	2	0.6%
87	3	0.9%
86	3	0.9%
85	5	1.4%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	year	month	day	week	temp_2	temp_1	average	actual	forecast_noaa	forecast_acc	forecast_under	friend
0	2016	1	1	Fri	45	45	45.6	45	43	50	44	29
1	2016	1	2	Sat	44	45	45.7	44	41	50	44	61
2	2016	1	3	Sun	45	44	45.8	41	43	46	47	56
3	2016	1	4	Mon	44	41	45.9	40	44	48	46	53
4	2016	1	5	Tues	41	40	46.0	44	46	46	46	41
5	2016	1	6	Wed	40	44	46.1	51	43	49	48	40
6	2016	1	7	Thurs	44	51	46.2	45	45	49	46	38
7	2016	1	8	Fri	51	45	46.3	48	43	47	46	34
8	2016	1	9	Sat	45	48	46.4	50	46	50	45	47
9	2016	1	10	Sun	48	50	46.5	52	45	48	48	49

Last rows

	year	month	day	week	temp_2	temp_1	average	actual	forecast_noaa	forecast_acc	forecast_under	friend
338	2016	12	22	Thurs	51	49	45.1	45	42	47	46	38
339	2016	12	23	Fri	49	45	45.1	40	45	49	44	35
340	2016	12	24	Sat	45	40	45.1	41	44	47	46	39
341	2016	12	25	Sun	40	41	45.1	42	42	49	44	31
342	2016	12	26	Mon	41	42	45.2	42	45	48	46	58
343	2016	12	27	Tues	42	42	45.2	47	41	50	47	47
344	2016	12	28	Wed	42	47	45.3	48	41	49	44	58
345	2016	12	29	Thurs	47	48	45.3	48	43	50	45	65
346	2016	12	30	Fri	48	48	45.4	57	44	46	44	42
347	2016	12	31	Sat	48	57	45.5	40	42	48	47	57

Overview

Variables

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Phik (φk)

Missing values

Sample

First rows

Last rows